Abstract How do preferences for neighborhood amenities vary by income? Using data on over 100 million visits to 1.4 million establishments, I estimate a discrete choice model of demand for restaurants, shops, personal services, and entertainment places. While preferences for specific establishments often vary by income, preferences for neighborhoods' overall amenity access are highly aligned. The primary determinant is density: dense urban areas have sufficient variety to offer broad appeal. For incumbents of gentrifying neighborhoods, tailoring amenities to higher-income entrants has only modest welfare effects relative to the effects of potential displacement to cheaper neighborhoods with worse access to amenities.

Abstract The growth of the “gig” economy generates worker flexibility that, some have speculated, will favour women. We explore this by examining labour supply choices and earnings among more than a million rideshare drivers on Uber in the U.S. We document a roughly 7% gender earnings gap amongst drivers. We show that this gap can be entirely attributed to three factors: experience on the platform (learning-by-doing), preferences and constraints over where to work (driven largely by where drivers live and, to a lesser extent, safety), and preferences for driving speed. We do not find that men and women are differentially affected by a taste for specific hours, a return to within-week work intensity, or customer discrimination. Our results suggest that, in a “gig” economy setting with no gender discrimination and highly flexible labour markets, women’s relatively high opportunity cost of non-paid-work time and gender-based differences in preferences and constraints can sustain a gender pay gap.